Results 101 to 110 of about 8,956,383 (239)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Assessing Government Subsidies for Reducing Pesticide Use: A Meta‐Analysis

Applied Economic Perspectives and Policy, EarlyView.
ABSTRACT In the efforts being made by governments to reduce pesticide use, subsidies are an important instrument to encourage farmers to adopt more sustainable practices. Yet, their effectiveness remains uncertain due to diverse designs and contexts.
Gaëlle Leduc, Douadia Bougherara, Thi Thanh Mai Ha, Laure Latruffe   +3 more
wiley   +1 more source

Machine learning driven many‐objective moving horizon scheduling optimization

AIChE Journal, EarlyView.
Abstract Industrial electrification can decarbonize chemical manufacturing, but it exposes operations to volatile electricity prices and carbon intensities. This work develops a machine learning‐enhanced many‐objective moving horizon scheduling framework that predicts objective correlation groupings from 48‐hour price and emission‐intensity profiles ...
Hongxuan Wang, Andrew Allman
wiley   +1 more source

Shale Gas and the EU Internal Gas Market: Beyond the Hype and Hysteria. CEPS Working Document No. 369, September 2012 [PDF]

, 2012
This paper analyses the interplay between shale gas and the EU internal gas market. Drawing on data presented in the 2012 International Energy Agency’s report on unconventional gas and additional scenario analyses performed by the Joint Research Centre ...
Teusch, Jonas
core  

Natural Gas Pipeline Company of America, docket no. CP72-233, Sabine Pass Project.

, 1973
91 p.The administrative action here involved arises from an application filed by Natural Gas Pipeline Company of America (Natural) seeking authorization pursuant to Section 7 of the Natural Gas Act for a certificate of public convenience and necessity ...
U.S. Federal Power Commission, Bureau of Natural Gas
core   +1 more source

Machine learning–driven design of catalytic processes for sulfur dioxide oxidation: Lessons from the trenches

AIChE Journal, EarlyView.
Abstract Despite the growing use of ML in chemical engineering, the catalytic conversion of sulfur dioxide (SO2) to sulfur trioxide (SO3) remains underexplored from a data‐driven modeling perspective. This study evaluates an integrated workflow for literature‐derived SO2 oxidation data, combining data curation, preprocessing assessment, machine ...
Farough Agin, Jules Thibault, Clémence Fauteux‐Lefebvre   +2 more
wiley   +1 more source

Hydraulic-thermal decoupling simulation model for transient operation of natural gas pipeline networks

You-qi chuyun
ObjectiveThe transient operation simulation technology for natural gas pipeline networks is essential for peak shaving, economical and safe operation, and diagnosing abnormal service conditions.
Chunyu YU, Chunhao YU, Gang LIU, Rui LIU, Fang YANG, Yang QIN, Lili ZUO, Qian CHEN   +7 more
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Análise exergética dos modais de transporte de gás natural por gasodutos e por GNL [PDF]

, 2013
Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2013.A disponibilidade de gás natural normalmente ocorre em regiões distantes dos centros consumidores ...
Romanos, Rafael Reami
core  

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source